Duration: 1 Hour

Option 1: Tuesday, February 2^nd at 12:00pm ET

This session will have some interaction through polling and the chat function.

Course Description

This session covers two formidable hurdles to the effective use of AI in organizations.  First, it covers how bias arises in AI systems. It discusses why algorithmic fairness is difficult to define and summarizes some of the current discussions around definitions of algorithmic fairness. It also covers possible approaches to dealing with bias, including the use of synthetic data to achieve fairness. It discusses a number of reasons that bias is a formidable problem for organizations and raises the question of who in the organization should deal with these issues. Second, it turns to the closely related topic of “interpretability” in AI systems. It then connects the issue of interpretability to issues of regulation and bias.